Field experimental results of three‐component fiber‐optic seismic sensors
Bibliographic record
Abstract
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2000Field experimental results of three‐component fiber‐optic seismic sensorsAuthors: F. X. (Tad) BostickF. X. (Tad) BostickCiDRA Corporationhttps://doi.org/10.1190/1.1815889 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1815889FiguresReferencesRelatedDetailsCited ByA Literature Review10 December 2021Onland and Offshore Extrinsic Fabry–Pérot Optical Seismometer at the End of a Long Fiber9 October 2019 | Seismological Research Letters, Vol. 90, No. 6Imaging the Aquistore reservoir after 36 kilotonnes of CO2 injection using distributed acoustic sensingKyle Harris, Don White, and Claire Samson23 October 2017 | GEOPHYSICS, Vol. 82, No. 6Measuring seismic signals with airborne stereo camerasThomas Rapstine and Paul Sava17 August 2017A comparison of trenched distributed acoustic sensing (DAS) to trenched and surface 3C geophones - Daly, Manitoba, CanadaRob Kendall*5 August 2014Field testing of fiber-optic distributed acoustic sensing (DAS) for subsurface seismic monitoringThomas M. Daley, Barry M. Freifeld, Jonathan Ajo-Franklin, Shan Dou, Roman Pevzner, Valeriya Shulakova, Sudhendu Kashikar, Douglas E. Miller, Julia Goetz, Jan Henninges, and Stefan Lueth6 June 2013 | The Leading Edge, Vol. 32, No. 64D monitoring with permanent borehole seismic sensors: progress, challenges, and the road aheadBrian E. Hornby, Olav Barkved, Hans Sugianto, and Jay Nahm25 October 2012Passive "drive by" imaging in a deep water production well using permanent borehole seismic sensorsBrian E. Hornby and Tom Burch15 December 2008Onshore 4D seismic repeatability at the gas storage geophysical laboratoryP. Faure and S. Spitz6 October 2006Field test of a permanent in-well fiber-optic seismic systemBrian E. Hornby, F. X. (Tad) Bostick, Brock A. Williams, Kristen A. Lewis, and Paul G. Garossino7 July 2005 | GEOPHYSICS, Vol. 70, No. 4Fiber optic 4C seabed cable field trialsS. Maas, J. Bunn, B. Bunn, R. Metzbower, J. Bowlus, and J. Bielinski3 January 2005Converted‐wave seismic exploration: MethodsRobert R. Stewart, James E. Gaiser, R. James Brown, and Don C. Lawton17 September 2002 | GEOPHYSICS, Vol. 67, No. 5Changing paradigms in oil and gas reservoir monitoring - the introduction and commercialization of in-well optical sensing systems SEG Technical Program Expanded Abstracts 2000ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2000 Pages: 2484 publication data© 2000 Copyright © 2000 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 04 Jan 2005 CITATION INFORMATION F. X. (Tad) Bostick, III, (2000), "Field experimental results of three‐component fiber‐optic seismic sensors," SEG Technical Program Expanded Abstracts : 21-24. https://doi.org/10.1190/1.1815889 Plain-Language Summary PDF DownloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".